Mapping Oyster Reef Distribution Using Kompsat-2/3 and Linear Spectral Unmixing Algorithm - A Case Study at Hwangdo Tidal Flat
Kim, K.-L. and Ryu, J.-H., 2020. Mapping oyster reef distribution using Kompsat-2/3 and linear spectral unmixing algorithm – A case study at Hwangdo tidal flat. In: Jung, H.-S.; Lee, S.; Ryu, J.-H., and Cui, T. (eds.), Advances in Geospatial Research of Coastal Environments. Journal of Coastal Resea...
Gespeichert in:
Veröffentlicht in: | Journal of coastal research 2020-09, Vol.102 (sp1), p.246-253 |
---|---|
Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 253 |
---|---|
container_issue | sp1 |
container_start_page | 246 |
container_title | Journal of coastal research |
container_volume | 102 |
creator | Kim, Kye-Lim Ryu, Joo-Hyung |
description | Kim, K.-L. and Ryu, J.-H., 2020. Mapping oyster reef distribution using Kompsat-2/3 and linear spectral unmixing algorithm – A case study at Hwangdo tidal flat. In: Jung, H.-S.; Lee, S.; Ryu, J.-H., and Cui, T. (eds.), Advances in Geospatial Research of Coastal Environments. Journal of Coastal Research, Special Issue No. 102, pp. 246-253. Coconut Creek (Florida), ISSN 0749-0208. Oyster areas are widely used as species of biological indicator, and they are also the most important shellfish in terms of ecosystem economic valuation. Oysters are production on the west coast before 2007 accounted for about 5 % of the nation's total production, but the 2007 Hebei Spirit oil spill caused production to plunge to less than 1 %. Therefore, spatial distribution maps of oyster reefs are required to help local authorities define management strategies. In this study, Kompsat-2/3 was used to map oyster reef distribution and analyze the distribution of oyster reefs based on linear spctral unmixing in Hwangdo tidal flat. A spectral library, collected in situ for various conditions with a field spectroradiometer, was used to conduct linear spectral unmixing classifications on Kompsat-2/3 data. The classification result shows very high accuracy, with an overall accuracy of 95 % or more, and there were misclassifications in some areas. The most causes of misclassification are the similarity of spectral characteristics and the limitations of the spatial and spectral resolutions of satellite images. For this reason, it was difficult to distinguish between oyster reefs and area distributed with many macrobenthos, and small-young oyster reefs were difficult to classify due to very weak reflectivity. In addition, the sand bar, it was is difficult to distinguish between oyster reefs related to dead reefs and sandbars because of the high reflectivity of these areas in the imagery. As a result of analyzing the change in the oyster reef area, it increased in 2019 compared to that in 2015. Especially, the oyster reef area increased in 30-50 % sand content and decreased in 20-30 % and 60-70 %. The changes of sand sediment seem to affect the distribution of oyster reefs. This study may be useful for mapping the distribution of oyster reefs and understanding the spatial variation of their habitat. |
doi_str_mv | 10.2112/SI102-030.1 |
format | Article |
fullrecord | <record><control><sourceid>jstor_proqu</sourceid><recordid>TN_cdi_proquest_journals_2812407147</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><jstor_id>48639241</jstor_id><sourcerecordid>48639241</sourcerecordid><originalsourceid>FETCH-LOGICAL-b317t-f22cb1d1f1b4ad7a0fbc06f9200794e35f87a6d7e40fdd393365e5603ddf24ee3</originalsourceid><addsrcrecordid>eNp9kEtLAzEUhYMoWB8r10LAlcjozWMmM8tSrS1WBNuuh0yT1JR2MiYZtBt_u1MrLl3dxfedc-EgdEHglhJC76ZjAjQBBrfkAPVImpIkBZYdoh4IXiRAIT9GJyGsAEiWc9FDX8-yaWy9xC_bELXHr1obfG9D9LZqo3U1nocdfnKbJsiY0DuGZa3wxNZaejxt9CJ6ucbzemM_d2J_vXTexrcNTnAfD2TQeBpbtcUy4tGHrJfK4ZlVXWS4lvEMHRm5Dvr8956i-fBhNhglk5fH8aA_SSpGREwMpYuKKGJIxaUSEky1gMwUFEAUXLPU5EJmSmgORilWMJalOs2AKWUo15qdoqt9b-Pde6tDLFeu9XX3sqQ5oRwE4aKzbvbWwrsQvDZl4-1G-m1JoNwNXP4MXHYDl6SzL_f2KkTn_1SeZ6ygfMev97yyztX6365vlPiDcg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2812407147</pqid></control><display><type>article</type><title>Mapping Oyster Reef Distribution Using Kompsat-2/3 and Linear Spectral Unmixing Algorithm - A Case Study at Hwangdo Tidal Flat</title><source>JSTOR</source><creator>Kim, Kye-Lim ; Ryu, Joo-Hyung</creator><creatorcontrib>Kim, Kye-Lim ; Ryu, Joo-Hyung</creatorcontrib><description>Kim, K.-L. and Ryu, J.-H., 2020. Mapping oyster reef distribution using Kompsat-2/3 and linear spectral unmixing algorithm – A case study at Hwangdo tidal flat. In: Jung, H.-S.; Lee, S.; Ryu, J.-H., and Cui, T. (eds.), Advances in Geospatial Research of Coastal Environments. Journal of Coastal Research, Special Issue No. 102, pp. 246-253. Coconut Creek (Florida), ISSN 0749-0208. Oyster areas are widely used as species of biological indicator, and they are also the most important shellfish in terms of ecosystem economic valuation. Oysters are production on the west coast before 2007 accounted for about 5 % of the nation's total production, but the 2007 Hebei Spirit oil spill caused production to plunge to less than 1 %. Therefore, spatial distribution maps of oyster reefs are required to help local authorities define management strategies. In this study, Kompsat-2/3 was used to map oyster reef distribution and analyze the distribution of oyster reefs based on linear spctral unmixing in Hwangdo tidal flat. A spectral library, collected in situ for various conditions with a field spectroradiometer, was used to conduct linear spectral unmixing classifications on Kompsat-2/3 data. The classification result shows very high accuracy, with an overall accuracy of 95 % or more, and there were misclassifications in some areas. The most causes of misclassification are the similarity of spectral characteristics and the limitations of the spatial and spectral resolutions of satellite images. For this reason, it was difficult to distinguish between oyster reefs and area distributed with many macrobenthos, and small-young oyster reefs were difficult to classify due to very weak reflectivity. In addition, the sand bar, it was is difficult to distinguish between oyster reefs related to dead reefs and sandbars because of the high reflectivity of these areas in the imagery. As a result of analyzing the change in the oyster reef area, it increased in 2019 compared to that in 2015. Especially, the oyster reef area increased in 30-50 % sand content and decreased in 20-30 % and 60-70 %. The changes of sand sediment seem to affect the distribution of oyster reefs. This study may be useful for mapping the distribution of oyster reefs and understanding the spatial variation of their habitat.</description><identifier>ISSN: 0749-0208</identifier><identifier>EISSN: 1551-5036</identifier><identifier>DOI: 10.2112/SI102-030.1</identifier><language>eng</language><publisher>Fort Lauderdale: Coastal Education and Research Foundation</publisher><subject>Accuracy ; Algorithms ; Benthos ; Case studies ; Classification ; Coastal environments ; Coastal inlets ; Coastal research ; Coastal zones ; Distribution ; Indicator species ; Kompsat-2/3 ; linear spectral unmixing ; Mapping ; Marine molluscs ; Oil spills ; Oyster reef ; Oyster reefs ; Oysters ; Reefs ; Reflectance ; Sand ; Sand bars ; Satellite imagery ; Shellfish ; Spatial distribution ; Spatial variations ; Spectroradiometers ; tidal flat ; Tidal flats ; Zoobenthos</subject><ispartof>Journal of coastal research, 2020-09, Vol.102 (sp1), p.246-253</ispartof><rights>Coastal Education and Research Foundation, Inc. 2020</rights><rights>Copyright Allen Press Inc. Fall 2020</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-b317t-f22cb1d1f1b4ad7a0fbc06f9200794e35f87a6d7e40fdd393365e5603ddf24ee3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/48639241$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/48639241$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,780,784,803,27924,27925,58017,58250</link.rule.ids></links><search><creatorcontrib>Kim, Kye-Lim</creatorcontrib><creatorcontrib>Ryu, Joo-Hyung</creatorcontrib><title>Mapping Oyster Reef Distribution Using Kompsat-2/3 and Linear Spectral Unmixing Algorithm - A Case Study at Hwangdo Tidal Flat</title><title>Journal of coastal research</title><description>Kim, K.-L. and Ryu, J.-H., 2020. Mapping oyster reef distribution using Kompsat-2/3 and linear spectral unmixing algorithm – A case study at Hwangdo tidal flat. In: Jung, H.-S.; Lee, S.; Ryu, J.-H., and Cui, T. (eds.), Advances in Geospatial Research of Coastal Environments. Journal of Coastal Research, Special Issue No. 102, pp. 246-253. Coconut Creek (Florida), ISSN 0749-0208. Oyster areas are widely used as species of biological indicator, and they are also the most important shellfish in terms of ecosystem economic valuation. Oysters are production on the west coast before 2007 accounted for about 5 % of the nation's total production, but the 2007 Hebei Spirit oil spill caused production to plunge to less than 1 %. Therefore, spatial distribution maps of oyster reefs are required to help local authorities define management strategies. In this study, Kompsat-2/3 was used to map oyster reef distribution and analyze the distribution of oyster reefs based on linear spctral unmixing in Hwangdo tidal flat. A spectral library, collected in situ for various conditions with a field spectroradiometer, was used to conduct linear spectral unmixing classifications on Kompsat-2/3 data. The classification result shows very high accuracy, with an overall accuracy of 95 % or more, and there were misclassifications in some areas. The most causes of misclassification are the similarity of spectral characteristics and the limitations of the spatial and spectral resolutions of satellite images. For this reason, it was difficult to distinguish between oyster reefs and area distributed with many macrobenthos, and small-young oyster reefs were difficult to classify due to very weak reflectivity. In addition, the sand bar, it was is difficult to distinguish between oyster reefs related to dead reefs and sandbars because of the high reflectivity of these areas in the imagery. As a result of analyzing the change in the oyster reef area, it increased in 2019 compared to that in 2015. Especially, the oyster reef area increased in 30-50 % sand content and decreased in 20-30 % and 60-70 %. The changes of sand sediment seem to affect the distribution of oyster reefs. This study may be useful for mapping the distribution of oyster reefs and understanding the spatial variation of their habitat.</description><subject>Accuracy</subject><subject>Algorithms</subject><subject>Benthos</subject><subject>Case studies</subject><subject>Classification</subject><subject>Coastal environments</subject><subject>Coastal inlets</subject><subject>Coastal research</subject><subject>Coastal zones</subject><subject>Distribution</subject><subject>Indicator species</subject><subject>Kompsat-2/3</subject><subject>linear spectral unmixing</subject><subject>Mapping</subject><subject>Marine molluscs</subject><subject>Oil spills</subject><subject>Oyster reef</subject><subject>Oyster reefs</subject><subject>Oysters</subject><subject>Reefs</subject><subject>Reflectance</subject><subject>Sand</subject><subject>Sand bars</subject><subject>Satellite imagery</subject><subject>Shellfish</subject><subject>Spatial distribution</subject><subject>Spatial variations</subject><subject>Spectroradiometers</subject><subject>tidal flat</subject><subject>Tidal flats</subject><subject>Zoobenthos</subject><issn>0749-0208</issn><issn>1551-5036</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kEtLAzEUhYMoWB8r10LAlcjozWMmM8tSrS1WBNuuh0yT1JR2MiYZtBt_u1MrLl3dxfedc-EgdEHglhJC76ZjAjQBBrfkAPVImpIkBZYdoh4IXiRAIT9GJyGsAEiWc9FDX8-yaWy9xC_bELXHr1obfG9D9LZqo3U1nocdfnKbJsiY0DuGZa3wxNZaejxt9CJ6ucbzemM_d2J_vXTexrcNTnAfD2TQeBpbtcUy4tGHrJfK4ZlVXWS4lvEMHRm5Dvr8956i-fBhNhglk5fH8aA_SSpGREwMpYuKKGJIxaUSEky1gMwUFEAUXLPU5EJmSmgORilWMJalOs2AKWUo15qdoqt9b-Pde6tDLFeu9XX3sqQ5oRwE4aKzbvbWwrsQvDZl4-1G-m1JoNwNXP4MXHYDl6SzL_f2KkTn_1SeZ6ygfMev97yyztX6365vlPiDcg</recordid><startdate>20200901</startdate><enddate>20200901</enddate><creator>Kim, Kye-Lim</creator><creator>Ryu, Joo-Hyung</creator><general>Coastal Education and Research Foundation</general><general>Allen Press Publishing</general><general>Allen Press Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QF</scope><scope>7QL</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7T7</scope><scope>7TA</scope><scope>7TB</scope><scope>7TN</scope><scope>7U5</scope><scope>7U9</scope><scope>7XB</scope><scope>88I</scope><scope>8BQ</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>F28</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>H8D</scope><scope>H8G</scope><scope>H94</scope><scope>H96</scope><scope>HCIFZ</scope><scope>JG9</scope><scope>JQ2</scope><scope>KR7</scope><scope>L.G</scope><scope>L6V</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M2P</scope><scope>M7N</scope><scope>M7S</scope><scope>P64</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>Q9U</scope></search><sort><creationdate>20200901</creationdate><title>Mapping Oyster Reef Distribution Using Kompsat-2/3 and Linear Spectral Unmixing Algorithm - A Case Study at Hwangdo Tidal Flat</title><author>Kim, Kye-Lim ; Ryu, Joo-Hyung</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-b317t-f22cb1d1f1b4ad7a0fbc06f9200794e35f87a6d7e40fdd393365e5603ddf24ee3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Accuracy</topic><topic>Algorithms</topic><topic>Benthos</topic><topic>Case studies</topic><topic>Classification</topic><topic>Coastal environments</topic><topic>Coastal inlets</topic><topic>Coastal research</topic><topic>Coastal zones</topic><topic>Distribution</topic><topic>Indicator species</topic><topic>Kompsat-2/3</topic><topic>linear spectral unmixing</topic><topic>Mapping</topic><topic>Marine molluscs</topic><topic>Oil spills</topic><topic>Oyster reef</topic><topic>Oyster reefs</topic><topic>Oysters</topic><topic>Reefs</topic><topic>Reflectance</topic><topic>Sand</topic><topic>Sand bars</topic><topic>Satellite imagery</topic><topic>Shellfish</topic><topic>Spatial distribution</topic><topic>Spatial variations</topic><topic>Spectroradiometers</topic><topic>tidal flat</topic><topic>Tidal flats</topic><topic>Zoobenthos</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kim, Kye-Lim</creatorcontrib><creatorcontrib>Ryu, Joo-Hyung</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Aluminium Industry Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Science Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Engineering Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><jtitle>Journal of coastal research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kim, Kye-Lim</au><au>Ryu, Joo-Hyung</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Mapping Oyster Reef Distribution Using Kompsat-2/3 and Linear Spectral Unmixing Algorithm - A Case Study at Hwangdo Tidal Flat</atitle><jtitle>Journal of coastal research</jtitle><date>2020-09-01</date><risdate>2020</risdate><volume>102</volume><issue>sp1</issue><spage>246</spage><epage>253</epage><pages>246-253</pages><issn>0749-0208</issn><eissn>1551-5036</eissn><abstract>Kim, K.-L. and Ryu, J.-H., 2020. Mapping oyster reef distribution using Kompsat-2/3 and linear spectral unmixing algorithm – A case study at Hwangdo tidal flat. In: Jung, H.-S.; Lee, S.; Ryu, J.-H., and Cui, T. (eds.), Advances in Geospatial Research of Coastal Environments. Journal of Coastal Research, Special Issue No. 102, pp. 246-253. Coconut Creek (Florida), ISSN 0749-0208. Oyster areas are widely used as species of biological indicator, and they are also the most important shellfish in terms of ecosystem economic valuation. Oysters are production on the west coast before 2007 accounted for about 5 % of the nation's total production, but the 2007 Hebei Spirit oil spill caused production to plunge to less than 1 %. Therefore, spatial distribution maps of oyster reefs are required to help local authorities define management strategies. In this study, Kompsat-2/3 was used to map oyster reef distribution and analyze the distribution of oyster reefs based on linear spctral unmixing in Hwangdo tidal flat. A spectral library, collected in situ for various conditions with a field spectroradiometer, was used to conduct linear spectral unmixing classifications on Kompsat-2/3 data. The classification result shows very high accuracy, with an overall accuracy of 95 % or more, and there were misclassifications in some areas. The most causes of misclassification are the similarity of spectral characteristics and the limitations of the spatial and spectral resolutions of satellite images. For this reason, it was difficult to distinguish between oyster reefs and area distributed with many macrobenthos, and small-young oyster reefs were difficult to classify due to very weak reflectivity. In addition, the sand bar, it was is difficult to distinguish between oyster reefs related to dead reefs and sandbars because of the high reflectivity of these areas in the imagery. As a result of analyzing the change in the oyster reef area, it increased in 2019 compared to that in 2015. Especially, the oyster reef area increased in 30-50 % sand content and decreased in 20-30 % and 60-70 %. The changes of sand sediment seem to affect the distribution of oyster reefs. This study may be useful for mapping the distribution of oyster reefs and understanding the spatial variation of their habitat.</abstract><cop>Fort Lauderdale</cop><pub>Coastal Education and Research Foundation</pub><doi>10.2112/SI102-030.1</doi><tpages>1</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0749-0208 |
ispartof | Journal of coastal research, 2020-09, Vol.102 (sp1), p.246-253 |
issn | 0749-0208 1551-5036 |
language | eng |
recordid | cdi_proquest_journals_2812407147 |
source | JSTOR |
subjects | Accuracy Algorithms Benthos Case studies Classification Coastal environments Coastal inlets Coastal research Coastal zones Distribution Indicator species Kompsat-2/3 linear spectral unmixing Mapping Marine molluscs Oil spills Oyster reef Oyster reefs Oysters Reefs Reflectance Sand Sand bars Satellite imagery Shellfish Spatial distribution Spatial variations Spectroradiometers tidal flat Tidal flats Zoobenthos |
title | Mapping Oyster Reef Distribution Using Kompsat-2/3 and Linear Spectral Unmixing Algorithm - A Case Study at Hwangdo Tidal Flat |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-03T15%3A01%3A16IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-jstor_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Mapping%20Oyster%20Reef%20Distribution%20Using%20Kompsat-2/3%20and%20Linear%20Spectral%20Unmixing%20Algorithm%20-%20A%20Case%20Study%20at%20Hwangdo%20Tidal%20Flat&rft.jtitle=Journal%20of%20coastal%20research&rft.au=Kim,%20Kye-Lim&rft.date=2020-09-01&rft.volume=102&rft.issue=sp1&rft.spage=246&rft.epage=253&rft.pages=246-253&rft.issn=0749-0208&rft.eissn=1551-5036&rft_id=info:doi/10.2112/SI102-030.1&rft_dat=%3Cjstor_proqu%3E48639241%3C/jstor_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2812407147&rft_id=info:pmid/&rft_jstor_id=48639241&rfr_iscdi=true |